基于包含润滑油填充率的Reynolds 方程和Greenwood-Tripp 微凸峰接触理论，采用质量守恒边界条件，通过使用有限差分法和有限元法联立求解热弹性流体润滑的各控制方程，以某高功率密度柴油机的主轴承为例进行热弹性流体混合润滑研究．通过分析功率密度升高对轴承性能的影响机理，确定需改进的结构参数，考察了油孔位置、椭圆形油孔、轴瓦表面粗糙度和润滑油油品对轴承润滑性能的影响，最终通过合理匹配结构参数使得轴承最小油膜厚度增加了45.04% ，峰值粗糙接触压力减小了76.85% ，平均粗糙摩擦损失功率减小了76.62% ．得到结论：最大剪切率是评价轴承润滑性能的重要指标，表面粗糙度对油膜振荡有遏制作用，油孔对轴承润滑性能具有很大的影响，以及合理匹配结构参数对轴承设计具有重要意义．

为防止水下排气柴油机发生海水倒灌事故，需弄清水下排气管内海水倒流发生的物理机制与发生条件．通过管内径为90mm、长度为1.8m 的水平玻璃管在1、2 及3m 不同水深下排气的试验，获得了水下排气管倒流极限以及排气口水深变化对其影响．结果表明：在一定排气量范围内水相会在排气管出口端下部稳定地滞留一定长度，但不会形成实质的水倒流；随管内滞留水长度由0 增至1.8m，对应的极限表观气速由24m/s 降至8m/s，极限Wallis参数由0.95 降至0.55，倒流极限呈现出先快速减小后趋于定值的趋势；在相同管内滞留水长度随排气口水深增大，极限表观气速略有减小，而极限Wallis 参数基本不变，表明Wallis 参数较好地表征了排气密度和排气速度对水下排气管倒流极限的综合影响．

为了提高发动机动态转矩估计精度，提出了基于零维燃烧模型的增压柴油机转矩在线预测方法．首先从增压柴油机动态燃烧特性出发，分析了影响动态指示转矩的因素；通过稳态和动态试验获取燃烧放热率参数，并利用神经网络训练出工况参数与燃烧模型参数的关系式，得到能够预测燃烧放热规律的燃烧模型；然后在此基础上对缸内热力过程进行数值求解和算法简化，实现了在线指示转矩估计，具有良好的实时性．由于该方法解耦了工况参数与指示转矩之间的强非线性关系，获得了较高的预测精度，稳态平均相对误差为2%，动态平均相对误差为5%．

在一台改装的直列双缸柴油机上，将进气由空气改为比热比更高的氩气和氧气的混合气，研究了氩氧及空气氛围下天然气发动机的热平衡和㶲平衡。结果表明：相比于空气氛围，氩氧氛围下发动机的热效率和㶲效率都有显著的提高，且随着氩气比例的升高，这种优势更加明显。试验工况下，氩气氛围下热效率和㶲效率最高分别达到了47.8%和41.6%，相对空气氛围提升了40%（相对值）。氩氧和空气氛围下发动机热损失和㶲损失的分布也明显不同，氩氧氛围热损失和㶲损失比例最高的都存在于传热这部分，数值分别是33.6%和30.5%，而空气氛围下主要在排气这部分，数值分别为33.1%和16.4%。

该论文已在芬兰赫尔辛基举行的第28届CIMAC大会上发表。论文的版权归CIMAC所有。High efficiency, low cost of the fuel and long lifespan are the guaranty for low speed diesel engines to be the solution in many application areas like power generation or marine propulsion. On the other side low speed diesel engines show reduced availability when compared to steam turbines or, in a less grade, to gas turbines. The state of mechanical parts as piston, cylinders, rings, valves or injectors is solved usually through the operational maintenance, where detailed knowledge of turbocharger vibrations is not usually at disposal. This paper shows the performance and main features of a diagnosis system currently in service on four 14 MW-125 rpm ten cylinders, two stroke uniflow-scavenged diesel generators. The system captures and processes the information provided by 17 sensors: one accelerometer per cylinder head, one accelerometer per each turbocharger, one pick-up for each turbocharger for rpm measurement, one pick-up for instantaneous engine speed at fly wheel and one instantaneous torque sensor formed by strange gages located in the shaft between engine and generator. The diagnosis system is based on data-driven techniques supported by the historical data of the diesel generator at good condition. For the engine, the system captures about one thousands of engine cycle per day and applies windowing to every relevant engine process which allows the supervision of the following events: Engine: needle injector opening, needle injector closing, start of injection angle, end of injection angle, combustion roughness, compression stroke, expansion stroke, inlet port opening, exhaust valve closing, indicated torque harmonics. Generator: harmonics of the generator rotor oscillation. It has been demonstrated that harmonics 24th, 48th, 72th and 96th are related to the transitory torque generated by the passing of the rotor armature in front of the stator and therefore to its technical condition. For the turbochargers, the analysis is performed for a package of 80 consecutive turbocharger cycles which allows the supervision of the following events: Turbocharger: Engine Power-Turbocharger rpm curve, bearing vibration harmonics, turbocharger shaft vibration harmonics. Each event is characterized by an indicator (harmonic amplitude, root mean square acceleration amplitude at specific frequency band, torque and angular speed amplitude at specific frequency band, mean turbocharger speed). The reference condition is evaluated from the event indicator-power data map at good condition which is gathered after engine overhaul or after the replacement of the component. The condition of the engine generator is evaluated from the evolution of the symptom named SINDEX along operational hours of the generator: SINDEX = 2 • abs[Ic (W) - It max (W)] / [It max (W) + It min (W)] if Ic (W) > It max (W) SINDEX = 2 • abs[Ic (W) - It min (W)] / [It max (W) + It min (W)] if Ic (W) < It min (W) Being I the event indicator, W generator power, suffix c the current value, suffix t the reference template value and max and min refers to the maximum and minimum values of the indicators template for every generator power band. The system is working from 2012 in one group and from 2015 in the three identical diesel groups at Diesel Power Plant of Mahón (Balearic Island, Spain). Up to now the system has identified the following anomalies: • Cylinder seizure (3) • Broken rings (9) • Injector malfunction (5) • Changing of the start of injection (3) • Exhaust valve regulator failure (2) • Turbine blade failure (1) • Compressor fouling (continuously) Work is in progress to increase the capability of the system to identify combustion anomalies that will be developed before 28th CIMAC Congress.

该论文已在芬兰赫尔辛基举行的第28届CIMAC大会上发表。论文的版权归CIMAC所有。The recent advancement in computer performances and the developed machine learning algorithm have been bringing us to the more sophisticated abnormality detection and condition diagnosis based on big data analysis. These results have also been required to seek safer and more economical operations. However, when it comes to the machineries in the engine room in a ship, the practical diagnostic system that gives sufficient economic effects does not seem to prevail because: • The engine room consists of a number of machineries of different manufacturers, each of which must be equipped with its own diagnostic system; • The diagnostic system for smaller machineries in particular is less likely to be developed due to a lack of expected cost effectiveness; or • The measurement items for the engine system lack unified standards for data format, impeding the development of multi-purpose systems. To find a solution to the abovementioned problems, the mechanism equipped with the following functions has been developed: • A diagnostic platform applicable to diverse machineries and equipped with the support functions for the automatic abnormality detection, automatic condition diagnosis and automatic troubleshooting; • The application of the automatic abnormality detection algorithm based on machine learning and the establishment of the optimal method to apply the algorithm to each vessel machinery; • The integration of the measured data and diagnostic results of each machinery with maintenance and management; and • The function for the uniform management and effective use of the aforementioned information. A field test has been conducted witnessed by multiple machinery manufacturers for the purpose of diagnosing the all engine room machineries. The test has been indicating the originally anticipated effects. The previous system has been applied to the practical ships in the last few years, with the majority of problems already solved indicating the effectiveness of this concept. Machinery manufacturers can apply this platform to those machineries for which no diagnostic system was developed for the cost-effectiveness reasons. The platform also helps users uniformly control a number of different machineries through a single system and easily have an advanced diagnosis from the specialist of machinery manufacturers. This study aims to further increase the accuracy in data analysis and support safer and more economical operations using diagnostic results. The study can also develop the platform such that it will be applicable not only to the engine room machineries but to the ship as a whole, rather than showing versatile diagnostic functions.

该论文已在芬兰赫尔辛基举行的第28届CIMAC大会上发表。论文的版权归CIMAC所有。Large amount of G-type and S-type engines of the latest generation have entered service successfully. These engines are in general characterized by Tier II compliance, typically they have heavily derated layouts and they have performance with main focus on part & low load fuel optimisation. Very close to 100% of these engines are electronically controlled ME-C&ME-B types. This paper will describe an update on service experience for this generation of engines. Topics touched upon will be electronic and hydraulic issues for the ME-engines, cylinder condition mainly focussing on cold corrosion control, issues related to structural integrity and also bearing performance. Furthermore early service experience for the high pressure gas injection ME-GI engines will be shared. Also service experience for Tier III compliant engines with Exhaust Gas Recirculation (EGR) or Selective Catalytic Reaction (SCR) will be presented.

该论文已在芬兰赫尔辛基举行的第28届CIMAC大会上发表。论文的版权归CIMAC所有。The 2-stroke low speed engines with high BMEP are particularly sensitive to cold corrosion. It depends, among other factors, upon the sulphur content of the fuel, the operating load, and the lube oil feed rate. The cold corrosion occurrence can lead to corrosive wear and, as a matter of fact, to strong damages for the engine liners. To avoid failures, the engine manufacturers (OEMs) recommend monitoring on a regular basis the engine by checking the residual base number (BN) and the iron content (Fe) of the cylinder lube oil (CLO) sampled at the bottom of the liners. The BN and the Fe are generally determined by on-shore laboratory analysis because reliable techniques and standardized procedures are applied. However the timing to get the information while in operation is extended and sometime inappropriate to prevent engine failures. Therefore alternative solutions for BN and Fe determination on-board are proposed to the users. But sometime such alternatives are time consuming for the crews, require particular skills or are still questioned for their reliability. The advantage of doing the BN and Fe analysis onboard is then counterbalanced by the risk of taking inappropriate actions. We propose an alternative that combines the advantages of the existing solutions and provides additional perspectives. It is an on-line system that ensures the automatic sampling of the lubricant from the cylinder units, the continuous determination of 6 parameters including the BN and the Fe, the processing and the reporting of the data with indications on actions to take if necessary. This On-line Reporting System (ORS) combines novel sensors and a genuine automatic sampling system. It stands in small volume, is simply connected to the drain oil pipes and operates without particular maintenance (no additional work for the crew). The ORS maintenance and update is based on an exchange of parts or sensors if necessary and on regular upgrade of the software. The ORS is ideal for the chief engineer to monitor in real time the critical parameters of the CLO on-board the vessel, but for the fleet managers as well because data can be sent on-shore. In a basic configuration, the data are acquired continuously, processed and finally visualized in the engine room by using the vessel management IT system. However more sophisticated data treatment and management can be tuned upon user needs. Therefore the ORS is a very powerful tool to prevent corrosive wear, but also to finely optimize the LOFR according to the actual vessel environment or sailing condition. In this paper we describe the ORS and how it operates. We review the parameters measured and we show the reliability of the measurements. We report on the tests in service during long haul voyages of the vessel. We finally propose various ways to value the data provided by the ORS.

该论文已在芬兰赫尔辛基举行的第28届CIMAC大会上发表。论文的版权归CIMAC所有。All low speed engine users face the problem of controlling abrasive wear and cold corrosion. With good reasons the producers of this type of engine recommend a Drain Oil analysis. Only frequent tests provide users with an accurate measure of the wear conditions within the cylinder. Not only is the Base Number of the Drain Oil important but also the iron content. The iron particles in the oil correspond with abrasive wear. Whereas Fe2+ and Fe3+ compounds show the amount of cold corrosion. Despite all that, the engine producers make no On Board Test Set available. However, several On Board Test Sets exist on the free market. It’s an advantage that these Test Sets only take a few minutes to provide a result of abrasive wear and cold corrosion. A laboratory will hand out the results after a few days or weeks after the sampling due to the shipment of the oil. Some of the On Board Sets only give the total iron content. And there are additional differences between the available test Sets. These differences affect mainly the handling, the cost, the accuracy and the analysis method itself. This list of differences also displays the common disadvantages and problems every operator has to handle with. Even though all these problems are common knowledge to ship owners and operators, no comparison or dissertation can be found. Furthermore a standardization of On Board Test Sets is not in sight. This paper gives a general view of the basic analysis methods and a selection of On Board Test Sets. It is important to outline a first comparison of these products and their methods. Additionally this paper sketches a possible future solution.

该论文已在芬兰赫尔辛基举行的第28届CIMAC大会上发表。论文的版权归CIMAC所有。The coming into force of the IMO TIER III requirements have brought many problems for the Engine Users with the conversion of engines to use new fuels plus the need for new lubricating oils to suit these new fuels. At the time of writing the operation of dual-fuel engines is not guaranteed 100%. All of this represents changes and uncertainties for the Users when the turbocharging situation, especially on 4-S engines and blower failures on 2-S engines have not been fully resolved. In addition, the use of exhaust gas scrubbers, is not yet a certainty for many. In the European Emission Control Area (ECA) only one case has been recorded so far where Exxon HDMA 50 fuel was mixed with HFO. That gave asphaltenes fall out and the storage tank had to be cleaned manually. With the HFO limited to only 4.0% (not a realistic figure on board ship) the storage tank still needed stripping. Therefore, in the longterm ship operators cannot live with different brands of fuel oil. There must be an ISO Standard which would ensure the mixability of new fuel grades. Such an ISO Standard must be so that it can fixed within a charter party while quality control and international supply will be the same at every port. The RND 80 mix, according to the ISO Standard 8217, may be the future standard as proposed by many suppliers. At the same time, there are quite a number of problems with large 4-S engines using Marine Gas Oil (MGO) when operating in ECA’s. An example of this is that fuel leaks into the lube oil trunk at a rate of up to 1.5 tonne in 7 hours. Therefore, there is a distinct risk of bearing failures or fire in the lube trunk. The oil cooling system for the fuel injectors is also under investigation. All of this means increased costs to the operator (the Engine User) at a time when all costs are rising and profits are often in decline.